cleanup for 2.0 release

README.md

@@ -4,7 +4,7 @@ This library processes crowdsourcing results from Amazon Mechanical Turk and Cro
 
 ## Installation
 
-To install the stable version from PyPI,  *pip* for your OS, then install using `pip install crowdtruth`
+To install the stable version from PyPI, *pip* for your OS, then install using `pip install crowdtruth`
 
 To install the latest version from source, download the library and install it using `python setup.py develop`
 

crowdtruth/models/metrics.py

@@ -217,8 +217,6 @@ def relation_quality_score(relations, work_sent_rel_dict, sqs, wqs):
 
     @staticmethod
     def run(results, config, max_delta = 0.001):
-
-        logging.info("Using experimental version a2")
 
         judgments = results['judgments'].copy()
         units = results['units'].copy()

setup.py

@@ -2,23 +2,43 @@
 import sys, os
 
 setup(name='crowdtruth',
-    version='2.0-alpha.1',
+    version='2.0',
     description="Disagreement based metrics for the processing and evaluation of crowdsourced annotations",
-    long_description="CrowdTruth is an approach to machine-human computing for collecting annotation data on text, images and videos. The approach is focussed specifically on collecting gold standard data for training and evaluation of cognitive computing systems. The original framework was inspired by the IBM Watson project for providing improved (multi-perspective) gold standard (medical) text annotation data for the training and evaluation of various IBM Watson components, such as Medical Relation Extraction, Medical Factor Extraction and Question-Answer passage alignment.",
-    classifiers=[],
+    long_description="CrowdTruth is an approach to machine-human computing for collecting annotation data on text, images and videos. The approach is focussed specifically on collecting annotation data by capturing and interpreting inter-annotator disagreement. ",
+    classifiers = [
+        'Development Status :: 4 - Beta',
+        'Intended Audience :: Developers',
+        'Intended Audience :: Education',
+        'Intended Audience :: Information Technology',
+        'Intended Audience :: Science/Research',
+        'License :: OSI Approved :: Apache Software License',
+        'Operating System :: OS Independent',
+        'Programming Language :: Python :: 2.7',
+        'Programming Language :: Python :: 3.4',
+        'Programming Language :: Python :: 3.5',
+        'Programming Language :: Python :: 3.6',
+        'Topic :: Scientific/Engineering',
+        'Topic :: Scientific/Engineering :: Artificial Intelligence',
+        'Topic :: Scientific/Engineering :: Human Machine Interfaces',
+        'Topic :: Scientific/Engineering :: Information Analysis',
+        'Topic :: Text Processing',
+        'Topic :: Text Processing :: Filters',
+        'Topic :: Text Processing :: General',
+        'Topic :: Text Processing :: Indexing',
+        'Topic :: Text Processing :: Linguistic'],
     keywords=['CrowdTruth','crowdsourcing','disagreement','metrics','crowdflower','amazon mechanical turk'],
     author='Vrije Universiteit Amsterdam',
     author_email='crowdwatson@gmail.com',
     url='http://crowdtruth.org',
     license='Apache 2.0',
-    download_url = 'https://github.com/CrowdTruth/CrowdTruth-core/archive/v2.0-alpha.1.tar.gz',
+    download_url = 'https://github.com/CrowdTruth/CrowdTruth-core/archive/v2.0.tar.gz',
     packages=find_packages(exclude=['ez_setup', 'examples', 'tests']),
     include_package_data=True,
     zip_safe=False,
     test_suite='nose.collector',
     install_requires=[
         'pymodm>=0.3.0',
-        'pandas'
+        'pandas>=0.23.1'
         ],
     setup_requires=[],
     entry_points="""